Package de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch

BIRCH clustering.

See: Description

Interface Summary

Interface	Description
BIRCHAbsorptionCriterion	BIRCH absorption criterion.
BIRCHDistance	Distance function for BIRCH clustering.

Class Summary

Class	Description
AverageInterclusterDistance	Average intercluster distance.
AverageInterclusterDistance.Parameterizer	Parameterization class.
AverageIntraclusterDistance	Average intracluster distance.
AverageIntraclusterDistance.Parameterizer	Parameterization class.
BIRCHLeafClustering	BIRCH-based clustering algorithm that simply treats the leafs of the CFTree as clusters.
BIRCHLeafClustering.Parameterizer	Parameterization class.
CentroidEuclideanDistance	Centroid Euclidean distance.
CentroidEuclideanDistance.Parameterizer	Parameterization class.
CentroidManhattanDistance	Centroid Manhattan Distance Reference: Data Clustering for Very Large Datasets Plus Applications T.
CentroidManhattanDistance.Parameterizer	Parameterization class.
CFTree	Partial implementation of the CFTree as used by BIRCH.
CFTree.Factory	CF-Tree Factory.
CFTree.Factory.Parameterizer	Parameterization class for CFTrees.
CFTree.LeafIterator	Iterator over leaf nodes.
CFTree.TreeNode	Inner node.
ClusteringFeature	Clustering Feature of BIRCH
DiameterCriterion	Average Radius (R) criterion.
DiameterCriterion.Parameterizer	Parameterization class
EuclideanDistanceCriterion	Distance criterion.
EuclideanDistanceCriterion.Parameterizer	Parameterization class
RadiusCriterion	Average Radius (R) criterion.
RadiusCriterion.Parameterizer	Parameterization class
VarianceIncreaseDistance	Variance increase distance.
VarianceIncreaseDistance.Parameterizer	Parameterization class.

Package de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch Description

BIRCH clustering.